Rhabdomyosarcoma (RMS) is a highly malignant tumor of developing muscle that can occur anywhere in the body. Due to its rarity, relatively little is known about the epidemiology of RMS. Atopic disease is hypothesized to be protective against several malignancies; however, to our knowledge, there have been no assessments of atopy and childhood RMS. Therefore, we explored this association in a case-control study of 322 childhood RMS cases and 322 pair-matched controls. Cases were enrolled in a trial run by the Intergroup Rhabdomyosarcoma Study Group. Controls were matched to cases on race, sex and age. The following atopic conditions were assessed: allergies, asthma, eczema and hives; in addition, we examined other immune-related factors: birth order, day-care attendance and breastfeeding. Conditional logistic-regression models were used to calculate an odds ratio (OR) and 95% confidence interval (CI) for each exposure, adjusted for age, race, sex, household income and parental education. As the two most common histologic types of RMS are embryonal (n = 215) and alveolar (n = 66), we evaluated effect heterogeneity of these exposures. Allergies (OR = 0.60, 95% CI: 0.41–0.87), hives (OR = 0.61, 95% CI: 0.38–0.97), day-care attendance (OR = 0.48, 95% CI: 0.32–0.71) and breastfeeding for ≥ 12 months (OR = 0.36, 95% CI: 0.18–0.70) were inversely associated with childhood RMS. These exposures did not display significant effect heterogeneity between histologic types (p > 0.52 for all exposures). This is the first study indicating that atopic exposures may be protective against childhood RMS, suggesting additional studies are needed to evaluate the immune system’s role in the development of this tumor.

Acumen in Statistics

Erik Barry Erhardt, PhD, is an Associate Professor of Statistics at the University of New Mexico Department of Mathematics and Statistics, where he has served as Director of the Statistics Consulting Clinic, and is currently Director of the Biostatistics and NeuroInformatics (BNI) Core for the second phase of the Center for Biomedical Research Excellence (COBRE) in Brain Function and Mental Illness at the Mind Research Network. His research interests include Bayesian and Frequentist statistical methods for stable isotope sourcing and brain imaging. Erik is a Howard Hughes Medical Institute Interfaces Scholar collaborating in interdisciplinary research and offering consulting services in statistics.